Treatment Dropout Research Articles

Implementing group therapy for posttraumatic stress disorder within a primary care setting: A pilot study

BackgroundPosttraumatic stress disorder (PTSD) is associated with comorbid psychiatric and medical conditions and high rates of medical service utilization. Given that PTSD is highly prevalent in the primary care setting, group therapy delivered within this setting has the potential to treat large numbers of patients. To date, few studies have examined the feasibility or effectiveness of group therapy for PTSD within primary care. MethodsA pilot study of a PTSD group therapy intervention based on the Trauma Information Group model was conducted in a Federally Qualified Health Center (FQHC). Across 9 cohorts, 32 individuals with PTSD completed 8–10 group therapy sessions. Self-reported PTSD severity was assessed using the PTSD Checklist for DSM-5 (PCL-5) at baseline and post-treatment. ResultsFifty percent of participants had a PTSD treatment response (PCL-5 score reduction ≥10) following group therapy and paired t-tests demonstrated a statistically significant reduction in PCL-5 scores from pre- to post-treatment. Patient demographic characteristics and psychiatric comorbities were not associated with treatment response. LimitationsThe small sample size, demographic characteristics, and FQHC setting potentially limit the generalizability of these findings. Treatment dropout rates and associated factors also were not examined. ConclusionsThe Trauma Information Group treatment for PTSD was feasible to implement within a low resourced primary care setting and led to improvement in PTSD symptoms in this pilot study. These findings suggest that offering group therapy for PTSD within primary care could improve access to effective treatment and warrant future research to examine feasibility and effectiveness in this setting.

Intensive Treatment of Chronic Pain and PTSD: The PATRIOT Program.

Military combat can result in the need for comprehensive care related to both physical and psychological trauma, most commonly chronic pain and post-traumatic stress disorder (PTSD). These conditions tend to co-occur and result in high levels of distress and interference in everyday life. Thus, it is imperative to develop effective, time-efficient treatments for these conditions before they become chronic and resistant to change. We developed and pilot-tested the Pain and Trauma Intensive Outpatient Treatment (PATRIOT) Program, a brief, intensive (3 weeks, six sessions) integrated chronic pain and PTSD treatment. An overview and session-by-session outline of the PATRIOT Program is provided, followed by results from the first pilot evaluation of the PATRIOT Program's feasibility, acceptability, and preliminary efficacy in a sample of eight participating Veterans with comorbid chronic pain and PTSD. There were no treatment dropouts. At post-treatment, there were significant reductions in PTSD symptoms based on the Clinician-Administered Assessment of PTSD (CAPS). Pain and catastrophic thinking also decreased from pre- to post-treatment. With continued investigations and support, the PATRIOT Program may offer a brief, cost-effective, and more easily accessible treatment option for individuals who could benefit from learning skills to manage pain and PTSD more effectively.

Predicting dropout and non-response to psychotherapy for personality disorders: A study protocol focusing on therapist, patient, and the therapeutic relationship

BackgroundThe abandonment of psychotherapeutic treatments is influenced by various factors, including patient characteristics, therapist traits, and the therapeutic relationship. Despite the well-documented importance of these factors, limited empirical research has focused on the role of the therapeutic relationship and the characteristics of therapist-patient dyads in predicting treatment dropout. This study protocol outlines a longitudinal research project aimed at predicting dropout and non-response in psychotherapy for individuals with personality disorders. The research seeks to identify predictive factors related to psychotherapy outcomes, focusing on patient, therapist, and dyadic elements. Specifically, the study will examine the influence of therapist characteristics (e.g., personality traits, countertransference, responsiveness) on treatment outcomes, explore the impact of relational factors (e.g., treatment expectations, epistemic trust, therapeutic alliance) on therapy effectiveness, and assess how the therapeutic alliance within therapist-patient dyads affects the likelihood of dropout and non-response.MethodsThe longitudinal study will include 100 therapist-patient dyads (200 participants) recruited from various Mental Health Services in Milan, Italy. Validated instruments will be administered to both patients and therapists at four-time points: T0 (baseline), T1 (3 months), T2 (6 months), and T3 (1 year). Data will be collected at baseline and at the one-year mark to evaluate the relationships between therapist, patient, and dyadic factors and treatment outcomes.DiscussionIdentifying predictive variables associated with high dropout rates can help preempt treatment discontinuation, reducing the financial and operational burdens on mental health services. Understanding these factors will enable the development of targeted interventions to improve treatment engagement and reduce attrition. This approach could enhance outcomes for individuals with personality disorders and lead to more efficient resource allocation and sustainable delivery of mental health care.

Global Research Trends on Factors Affecting Tuberculosis (TB) Adherence and Dropout: A Bibliometric Study

ABSTRACT Tuberculosis (TB) remains one of the significant global health challenges, especially in resource-limited countries. Adherence to TB treatment is key to successful therapy and preventing the emergence of drug resistance. However, dropout rates or discontinuation of treatment before completion remains a major problem that needs to be addressed. This study aims to analyze global trends in research focusing on factors affecting TB treatment adherence and dropout through a bibliometric approach. Using the Publish or Perish application, relevant scientific articles with keywords such as treatment adherence, tuberculosis, treatment dropout, and influencing factors were searched from 2017 to 2024. A total of 50 articles from Google Scholar were further analyzed to identify by publication year, country, publisher, citation, and article type. The data was then processed using VOSviewer to visualize the relationship between keywords and research trends through Network Visualization, Overlay Visualization, and Density Visualization. The results of the analysis showed that Indonesia is the country with the highest number of publications, demonstrating a great commitment in addressing the TB challenge. Articles published in reputable journals, especially those adopting systematic and meta-analysis approaches, show great impact with a high number of citations. Bibliometric visualizations reveal that the focus of research lies on factors such as treatment, adherence, health workers, and access. In addition, family and community support was also found to be an important element in ensuring treatment adherence. In conclusion, this study emphasizes the need for a comprehensive and collaborative approach in improving TB treatment adherence and preventing dropouts. Further research in this area is needed to address existing gaps and develop more effective strategies in the fight against TB. Keywords: Treatment Adherence, Tuberculosis, Dropout, Influencing Factors, Health Worker

Efficacy and tolerability of extracorporeal shock wave therapy in patients with plantar fasciopathy: a systematic review with meta-analysis and meta-regression.

Plantar fasciopathy (PF) is a common musculoskeletal condition characterized by heel pain and functional impairment. Extracorporeal shock wave therapy (ESWT) has gained increasing interest in the treatment of PF, but the optimal ESWT program is still debated. Therefore, this systematic review with meta-analysis and meta-regression aimed at providing a comprehensive assessment of the efficacy and tolerability of ESWT in PF management. Randomized controlled trials (RCTs) published until February 2023 were systematically searched on PubMed/MEDLINE, Scopus, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), and PEDro. Studies assessing adult patients with PF treated with ESWT were considered. The primary outcome was the tolerability of ESWT, measured by treatment adherence, dropouts, and safety. Secondary outcomes were pain intensity and functional outcomes. Meta-analysis and meta-regression were performed to examine the relationship between ESWT program characteristics and treatment outcomes. The quality of included studies was assessed using the Jadad scale and the Cochrane risk-of-bias tool. Eleven studies met the inclusion criteria and were included in the analysis. Our findings showed that ESWT is effective in reducing pain intensity assessed by Visual Analogue Scale [focal-ESWT: -2.818 (SE 0.803, -4.393, -1.244; P< 0.0001; radial-ESWT: -3.038 (SE 0.428, -3.878, -2.199; P<0.001)]. Meta-regression analysis indicated a positive relationship between specific ESWT parameters (frequency, number of pulses, energy flux density and frequency, and number of pulses, pressure) and pain intensity (all P<0.05) and dropout (all P<0.05). ESWT seems to be an effective and tolerable treatment for PF, albeit the peculiarity of parameters might affect both the efficacy in pain relief and the adherence to the treatment. Physicians should consider individual patient characteristics when selecting the ESWT parameters for PF treatment. Further high-quality studies are warranted to establish the optimal ESWT protocol to treat PF.

Cancer care treatment attrition in adults: Measurement approaches and inequities in patient dropout rates – a rapid review

BackgroundCancer treatment attrition refers to the discontinuation of prescribed cancer therapies before completion. It can significantly impact patient outcomes and cancer survival rates making it a critical concern. There is growing evidence on inequalities in cancer care, the avoidable systematic differences in the health of different groups of people. Understanding the extent of treatment attrition, why it happens, for whom, and associated inequalities may improve cancer care delivery and patient outcomes.MethodsA rapid review was conducted to identify existing evidence on measures of cancer treatment attrition, definitions, reasons for attrition and potential inequalities. The review followed a systematic approach but with abbreviated processes to facilitate quicker evidence synthesis. Searches were restricted to MEDLINE and Embase databases from their inception dates to May 7, 2024. Additional searches were performed in PubMed, Google Scholar, and key grey literature from relevant organizations. Inclusion criteria were adults with any type of cancer undergoing treatment, with studies reporting quantitative or qualitative data on treatment attrition conducted outside of clinical trials. Exclusion criteria included studies on children or adolescents, clinical trials, non-English publications, and various non-research article types. Data extraction and quality assessment were performed using standardized tools, and studies were synthesized narratively.ResultsThe search retrieved 1,353 references, with 40 studies meeting inclusion criteria. Most studies were retrospective. Studies covered various cancer types and treatments, reporting measures of attrition and reasons for treatment drop-out. Factors influencing attrition included disease progression, death, clinical deterioration, treatment toxicity, and socioeconomic factors such as lower income or socioeconomic disadvantage.ConclusionsThis review highlights significant variability in how treatment attrition is measured and defined, and suggests potential inequalities in who discontinues treatment. Standardized measures of attrition and data collection on reasons for discontinuation are essential to improve cancer care outcomes and equity. Future research should focus on developing these standardized metrics and exploring interventions targeting identified disparities to support cancer patients to complete treatment and improve outcomes.

The relationship between emotion regulation difficulties and eating disorder outcomes: a longitudinal examination in a residential eating disorder treatment facility

ABSTRACT Eating disorders (EDs) are associated with numerous comorbidities and deleterious outcomes (e.g. medical complications, high rates of death by suicide). The complexities of EDs are further compounded by treatment dropout, poor treatment outcomes, and relapse. One way to better understand these complexities is to investigate broad, transdiagnostic risk factors that contribute to the etiology and maintenance of EDs, such as emotion regulation (ER) difficulties. We longitudinally tested the relationship between ER difficulties and ED outcomes in a sample of 101 female ED patients in a southeastern U.S. residential ED treatment facility. Consistent with hypothesis, there were significant improvements in both ER difficulties and eating pathology from admission to discharge. Further, improvement in ER difficulties was associated with improvements in eating pathology. These findings further substantiate the role of ER difficulties in eating disorders and provide further evidence for the relationship between ER difficulties and eating pathology among residential eating disorder patients.

Blunted anterior midcingulate response to reward in opioid users is normalized by prefrontal transcranial magnetic stimulation.

Abnormalities in goal-directed behavior, mediated by mesocorticolimbic reward function and structure, contribute to worse clinical outcomes including higher risk of treatment dropout and drug relapse in opioid users (OU). In a sham-controlled randomized study design, we measured whether robot-assisted 10Hz transcranial magnetic stimulation (TMS) applied to the prefrontal cortex was able to modulate anterior midcingulate cortex (MCC) electrophysiological response to rewards, in OU and matched healthy controls. We show that OU exhibit a blunted anterior MCC reward response, compared to healthy controls (t(39) = 2.62, p = 0.01, d = 0.84), and that this is normalized following 10-Hz excitatory TMS (t (36) = .82, p = 0.42, d = 0.17). Excitatory TMS modulated the putative reward function of the MCC in OU. Further work with increased sample sizes and TMS sessions is required to determine whether restoring MCC reward function increases reward-directed behaviors, which may enhance treatment success through the maintenance of treatment goals.

Not all types of depressed patients who persist with their antidepressant treatment improve in side effect complaints: A comparison of treatment completers and dropouts in the STAR*D trial.

There is a "traditional belief" that antidepressant side effect complaints improve with medication persistence; however, support for this theory has remained inconclusive. We aimed to examine if side effect complaints improved over time by modeling the relationship between side effect complaints and time at dropout for patients receiving citalopram during the first level of acute treatment in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial. We categorized the 2833 patients into five patterns by week of dropout. We used pattern-mixture modeling to model change in side effect complaints (frequency, intensity, and burden) over the 12-week course of treatment, while accounting for attrition and depressive severity. Using post-hoc linear contrasts, we compared the attrition patterns with the completers' pattern for severity of side effect complaints at each respective last visit prior to dropout as well as averaged side effect complaints across the duration of treatment. We also reported frequencies and tolerability of side effects for nine organ/function systems over the course of treatment. Patients who dropped out early exhibited worsening side effect burden and patients who dropped out later showed improvements in side effect frequency and intensity. Treatment completers improved in all side effect complaints over the course of treatment. Early attrition patterns had more severe side effect complaints for both tests of post-hoc linear contrasts than later attrition patterns and completers. Side effect complaints from antidepressant treatment improve over time, but only for some types of patients. As a precaution for early dropout, clinicians should monitor patients who exhibit worsening and more severe side effect complaints-especially in the first 6 weeks of antidepressant treatment. In addition, clinicians may want to consider changing the type of treatment early on for these patients, rather than encouraging them to persist with their current medication.

Effect of Relaxation-Based Virtual Reality on Psychological and Physiological Stress of Substance Abusers Under Detoxification: A Randomized Controlled Trial.

Substance abuse is a widespread problem, with high rates of treatment dropout. Stress plays a crucial role in this problem, so innovative interventions with stressed patients can assist them in completing treatment. This study is a randomized controlled trial with 60 participants who have substance abuse disorder undergoing detoxification at a residency facility in Tehran, Iran. Participants were randomly assigned to one of three groups: watching a 360° video of nature, a 360° video of a city environment, or no virtual experience. The intervention was performed only for one session. Psychological stress was measured using the Positive and Negative Affect Schedule and Perceived Stress Scale before and after the intervention. Physiological stress was assessed through respiratory rate, skin conductance, and heart rate recordings during the virtual reality (VR) experience. Data analysis was performed using R software (version 4.2). Paired t-test results indicated significant psychological differences before and after virtual nature experiences, but not in the control and city groups. The repeated measure ANOVA showed a significant reduction in skin conductance (p<0.01) and respiratory rate (p<0.01) scores in the nature group. The findings suggest that VR relaxation could be a potentially beneficial intervention for reducing stress in patients during detoxification.

Cognitive flexibility and emotion regulation in eating disorder patients with comorbid generalized anxiety and posttraumatic stress symptoms

ABSTRACT Research has found that difficulties in emotion regulation negatively impact mental health, whereas cognitive flexibility may promote stress resilience and positive mental health. Little is known about cognitive flexibility and emotion regulation in people with comorbid eating disorder (ED) and anxiety and stress disorders. A transdiagnostic ED population (N = 227) at an outpatient ED treatment facility completed several self-report instruments that measured cognitive flexibility, emotion regulation difficulties, posttraumatic stress disorder (PTSD) symptoms, and generalized anxiety disorder (GAD) symptoms upon admission. We investigated cognitive flexibility and emotion regulation differences for those with an ED without comorbidity and those with various combinations of comorbidity. In a one-way between-groups ANOVA, we investigated differences in cognitive flexibility for those with GAD, PTSD, neither, and both comorbidities. We found a statistically significant difference between these groups, with mean cognitive flexibility inventory scores being the lowest in the group with both comorbidities. However, when controlling for emotion regulation, a one-way between-groups ANCOVA indicated no significant differences in cognitive flexibility between comorbidity groups F(3, 222) = 1.20, p = .31 Partial η 2 = .02. Though self-reported cognitive flexibility levels differ among ED patients with and without comorbidities, it appears that these differences are better explained by emotion regulation. Therefore, addressing emotion regulation early in treatment for all individuals with EDs, regardless of comorbidity, is recommended as a future research focus to enhance treatment outcomes. Further research is needed to understand the impact of treating emotion regulation on ED treatment engagement, dropout, and effectiveness.

"The Decision to End Speech Therapy Brought More Peace and Tranquility Into Our Family": Exploring Speech-Related Treatment Fatigue and Dropout in Parents and Children With a Cleft Palate.

Treatment fatigue is a complex, multidimensional, multicausal, and subjective phenomenon that is not yet well explored and understood in the area of speech therapy. The purpose of this study was to investigate speech-related treatment fatigue and speech treatment dropout in parents and children with a cleft (lip and) palate receiving or having received speech treatment for cleft-related articulation disorders. Thirteen participants were included in this study (n = seven parents with a median age of 40 years and n = six children with a median age of 10 years). Qualitative semistructured interviews were conducted separately with parents and children to investigate their experiences with cleft speech treatment. An inductive thematic approach was used to analyze the data and construct different themes. Rigor of the data was verified by conducting an investigator triangulation and by performing member checks. The analyses of the interviews yielded three major themes of importance to the children and their parents: (a) physical symptoms of treatment fatigue, (b) psychological symptoms of treatment fatigue, and (c) from treatment fatigue to treatment dropout. Physical symptoms of treatment fatigue were mainly related to transportation burden. On a psychological level, speech treatment may potentially lead to a cognitive-emotional overload. These feelings are primarily related to the practical issue of scheduling required treatment sessions in the family agenda. The decision to discontinue speech treatment was reported to be multifactorial. In this decision-making process, data suggested that the child's perspective must be heard more.

No medication prescription and residential distance from the hospital are important factors associated with nonsurgical weight-loss treatment discontinuance in Japanese patients with high-degree obesity: a retrospective study

BackgroundAlthough the percentage of the population with a high degree of obesity (body mass index [BMI] ≥ 35 kg/m2) is low in Japan, the prevalence of obesity-related diseases in patients with high-degree obesity is greater than that in patients with a BMI < 35 kg/m2. Therefore, treatment for high-degree obesity is important. However, clinical studies have reported that 20–50% of patients with obesity discontinue weight-loss treatment in other countries. The circumstances surrounding antiobesity agents are quite different between Japan and other countries. In this study, we investigated the predictors of treatment discontinuation in Japanese patients with high-degree obesity.MethodsWe retrospectively reviewed the medical charts of 271 Japanese patients with high-degree obesity who presented at Toho University Sakura Medical Center for obesity treatment between April 1, 2014, and December 31, 2017. The patients were divided into non-dropout and dropout groups. Patients who discontinued weight-loss treatment within 24 months of the first visit were defined as “dropouts.” Multivariate Cox proportional hazards regression analysis and Kaplan–Meier survival analysis were performed to examine the factors predicting treatment withdrawal.ResultsAmong the 271 patients, 119 (43.9%) discontinued treatment within 24 months of the first visit. The decrease in BMI did not significantly differ between the two groups. No prescription of medication and residential distance from the hospital exceeding 15 km were the top contributors to treatment discontinuation, and the absence of prescription medication was the most important factor. The dropout-free rate was significantly higher in patients with medication prescriptions than in those without and in patients who lived within 15 km of the hospital than in those who lived farther than 15 km from the hospital.ConclusionsNo medication prescription and longer residential distance from the hospital were associated with treatment dropout in Japanese patients with high-degree obesity; therefore, the addition of antiobesity medications and telemedicine may be necessary to prevent treatment discontinuation in such patients.

Predictors and Patterns of Dropout From Psychiatric Treatment Among Trauma-Affected Refugees: A Large Data Pool Analysis.

Dropout from mental health treatment is a substantial hindrance to relevant and effective treatment. Despite the high prevalence of PTSD among refugees, research into their treatment dropout has received limited attention. This study aimed to identify patterns and predictors of treatment dropout versus completion through different treatment stages. The sample included 940 patients with a refugee background undergoing outpatient treatment for PTSD in Denmark. All patients were offered 10 medical doctor sessions and 16-20 psychotherapy sessions. Dropout was analysed in three stages: (1) during the first six MD sessions, (2) during the first eight psychotherapy sessions upon completion of Stage 1, and (3) during psychotherapy sessions 9 to 16. A stepwise multiple regression analysis was conducted for each stage to identify predictors of stage-specific dropout. Counter to expectations, both early dropout and full completion were associated with better symptom outcomes, relative to late-treatment dropout. Key predictors varied by stage, with younger age predicting early dropout, whereas chronic pain and poor Danish proficiency predicted late dropout. Female gender and a clearly articulated motivation for active participation were predictors for full treatment completion. Practical advice is suggested to accommodate at-risk patients and to re-evaluate patient engagement after familiarisation with treatment.

Efficacy of eHealth Versus In-Person Cognitive Behavioral Therapy for Insomnia: Systematic Review and Meta-Analysis of Equivalence.

Insomnia is a prevalent condition with significant health, societal, and economic impacts. Cognitive behavioral therapy for insomnia (CBTI) is recommended as the first-line treatment. With limited accessibility to in-person-delivered CBTI (ipCBTI), electronically delivered eHealth CBTI (eCBTI), ranging from telephone- and videoconference-delivered interventions to fully automated web-based programs and mobile apps, has emerged as an alternative. However, the relative efficacy of eCBTI compared to ipCBTI has not been conclusively determined. This study aims to test the comparability of eCBTI and ipCBTI through a systematic review and meta-analysis of equivalence based on randomized controlled trials directly comparing the 2 delivery formats. A comprehensive search across multiple databases was conducted, leading to the identification and analysis of 15 unique randomized head-to-head comparisons of ipCBTI and eCBTI. Data on sleep and nonsleep outcomes were extracted and subjected to both conventional meta-analytical methods and equivalence testing based on predetermined equivalence margins derived from previously suggested minimal important differences. Supplementary Bayesian analyses were conducted to determine the strength of the available evidence. The meta-analysis included 15 studies with a total of 1083 participants. Conventional comparisons generally favored ipCBTI. However, the effect sizes were small, and the 2 delivery formats were statistically significantly equivalent (P<.05) for most sleep and nonsleep outcomes. Additional within-group analyses showed that both formats led to statistically significant improvements (P<.05) in insomnia severity; sleep quality; and secondary outcomes such as fatigue, anxiety, and depression. Heterogeneity analyses highlighted the role of treatment duration and dropout rates as potential moderators of the differences in treatment efficacy. eCBTI and ipCBTI were found to be statistically significantly equivalent for treating insomnia for most examined outcomes, indicating eCBTI as a clinically relevant alternative to ipCBTI. This supports the expansion of eCBTI as a viable option to increase accessibility to effective insomnia treatment. Nonetheless, further research is needed to address the limitations noted, including the high risk of bias in some studies and the potential impact of treatment duration and dropout rates on efficacy. PROSPERO CRD42023390811; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=390811.

Analyzing Dropout in Alcohol Recovery Programs: A Machine Learning Approach.

Background: Retention in treatment is crucial for the success of interventions targeting alcohol use disorder (AUD), which affects over 100 million people globally. Most previous studies have used classical statistical techniques to predict treatment dropout, and their results remain inconclusive. This study aimed to use novel machine learning tools to identify models that predict dropout with greater precision, enabling the development of better retention strategies for those at higher risk. Methods: A retrospective observational study of 39,030 (17.3% female) participants enrolled in outpatient-based treatment for alcohol use disorder in a state-wide public treatment network has been used. Participants were recruited between 1 January 2015 and 31 December 2019. We applied different machine learning algorithms to create models that allow one to predict the premature cessation of treatment (dropout). With the objective of increasing the explainability of those models with the best precision, considered as black-box models, explainability technique analyses were also applied. Results: Considering as the best models those obtained with one of the so-called black-box models (support vector classifier (SVC)), the results from the best model, from the explainability perspective, showed that the variables that showed greater explanatory capacity for treatment dropout are previous drug use as well as psychiatric comorbidity. Among these variables, those of having undergone previous opioid substitution treatment and receiving coordinated psychiatric care in mental health services showed the greatest capacity for predicting dropout. Conclusions: By using novel machine learning techniques on a large representative sample of patients enrolled in alcohol use disorder treatment, we have identified several machine learning models that help in predicting a higher risk of treatment dropout. Previous treatment for other substance use disorders (SUDs) and concurrent psychiatric comorbidity were the best predictors of dropout, and patients showing these characteristics may need more intensive or complementary interventions to benefit from treatment.

Adherence to Short-Duration Treatment (3HP) for Latent Tuberculosis among International Migrants in Manaus, Amazonas: Evaluation of the Efficacy of Different Treatment Modalities.

Migration, a multifaceted phenomenon, has a significant impact on health. Migrants perform similar movement patterns within their country of origin, in transit, and in the country of destination, thus making it difficult to monitor TB treatment throughout the journey. The objective was to compare the effectiveness of different treatment modalities in adherence to the short-term regimen for LTBI (3HP) among international migrants and refugees. This is a quasi-experimental study conducted in Manaus-AM. The study population was made up of international migrants. The certification and monitoring of medication intake employed three strategies: self-administration (SA), directly observed conventional therapy (DOT), and Video Telemonitoring System for Tuberculosis Treatment (VDOT). The VDOT group and SA group exhibited the lowest rate of treatment dropout or interruption at 16.1%, followed by the DOT group at 23.1%. The results suggest that the most effective strategy for ensuring adherence among migrants and refugees was VDOT (OR_adj 0.26; CI 0.7-0.94), suggesting that migrants may be more likely to adhere to and complete their treatment. The results show that relying on different treatment strategies, adapted to the individuals' needs and risk factors, is a viable and effective way of providing person-centered TB care.

Identification of Psychological Treatment Dropout Predictors Using Machine Learning Models on Italian Patients Living with Overweight and Obesity Ineligible for Bariatric Surgery.

According to the main international guidelines, patients with obesity and psychiatric/psychological disorders who cannot be addressed to surgery are recommended to follow a nutritional approach and a psychological treatment. A total of 94 patients (T0) completed a battery of self-report measures: Symptom Checklist-90-Revised (SCL-90-R), Barratt Impulsiveness Scale-11 (BIS-11), Binge-Eating Scale (BES), Obesity-Related Well-Being Questionnaire-97 (ORWELL-97), and Minnesota Multiphasic Personality Inventory-2 (MMPI-2). Then, twelve sessions of a brief psychodynamic psychotherapy were delivered, which was followed by the participants completing the follow-up evaluation (T1). Two groups of patients were identified: Group 1 (n = 65), who fully completed the assessment in both T0 and T1; and Group 2-dropout (n = 29), who fulfilled the assessment only at T0 and not at T1. Machine learning models were implemented to investigate which variables were most associated with treatment failure. The classification tree model identified patients who were dropping out of treatment with an accuracy of about 80% by considering two variables: the MMPI-2 Correction (K) scale and the SCL-90-R Phobic Anxiety (PHOB) scale. Given the limited number of studies on this topic, the present results highlight the importance of considering the patient's level of adaptation and the social context in which they are integrated in treatment planning. Cautionary notes, implications, and future directions are discussed.

A cross-sector approach to explore socio-ecological associations with treatment engagement behaviours in Northern Ghana

BackgroundCancer presents a growing global burden, not least in African countries such as Ghana where high cancer treatment dropouts has been identified due to numerous social, cultural and financial reasons. There is little understanding regarding patterns of treatment access behaviour, especially in Northern Ghana, which this study was designed to explore. MethodsThrough cross-sector collaboration, we extracted and clinically validated cancer patient records available in the Tamale Teaching Hospital. These were analysed descriptively and through multi-variate logistic regression. A treatment mapping process was also applied to highlight challenges in data collection. Multiple imputation with chained equations was conducted for high levels of missing data. Sensitivity analysis was applied to assess the impact of missing data. ResultsTreatment drop-out was high even when uncertainty due to missing data was accounted for, and only 27 % of patients completely engaged with treatment. High drop-out was found for all cancers including those covered by the Ghana National Health Insurance scheme. Multi-variate logistic regression revealed that social, health condition and systemic factors influence treatment engagement until completion. High missing data was observed for liver, ovarian, colorectal, gastric, bladder, oesophageal and head and neck and skin cancers, and soft tissue sarcomas, which limited model fitting. ConclusionTreatment drop-out is a critical issue in Northern Ghana. There was high missing data due to the dynamic, complex and decentralised treatment pathway. Future studies are needed to understand the complex challenges in data recording. Policy summaryTreatment drop out is a pertinent issue that policy makers should look to address. Further discussion with stakeholders involved in cancer treatment and data collection is required to better understand challenges to routine data collection in the local setting. This will allow policy to be designed to cater for the impact of multiple intersecting health and social factors on treatment completion.

Association between depression severity, mental health recovery and dropout from behavioral health care treatment

BackgroundUnderstanding the relationship between depression severity, patient recovery, and treatment continuity may help optimize the delivery of behavioral health services. MethodsUsing Cox proportional hazards regression, this study measures the association between treatment dropout and baseline depression severity, as measured by the Patient Health Questionnaire (PHQ-9), and the association between treatment dropout and baseline recovery, as measured by the Recovery Assessment Scale (RAS). The study also explores heterogeneity by service line (general mental health, substance use disorder, and eating disorder), residential versus intermediate level of care setting, age groups (adolescent and adult), and dropout factors. The data include 14,689 patients treated at a multi-state behavioral health care provider, discharged between 2021 and 2022. Premature dropout from behavioral health care treatment for any cause, patient factors and administrative factors were used as separate outcomes. FindingsA unit increase in baseline PHQ-9 was associated with a 1.2% reduced treatment dropout risk (hazard ratio (HR): 0.988; 95% confidence interval [0.983–0.992]). A unit increase in baseline RAS score was associated with 0.5% increased dropout likelihood (HR: 1.005; 95% CI [1.004, 1.007]). Subgroup analyses show associations are driven by general mental health, adolescent, and intermediate level of care subgroups. Patients with higher baseline suicidality and lower willigness to ask for helphad a reduced risk of dropout. InterpretationPatients with greater depression severity and lower recovery scores at admission were more likely to stay in behavioral health treatment, especially among adolescents, patients with general mental health issues, and outpatients.